at Google ScholarTitle data
Duda, Sebastian ; Fabri, Lukas ; Kaymakci, Can ; Wenninger, Simon ; Sauer, Alexander:
Deriving Digital Energy Platform Archetypes for Manufacturing : A Data-Driven Clustering Approach.
In:
Proceedings of the 4th Conference on Production Systems and Logistics (CPSL). -
Santiago de Queretaro, Mexico
,
2023
Project information
| Project title: |
Project's official title Project's id Projektgruppe WI Digital Value Network No information Projektgruppe WI Nachhaltiges Energiemanagement & Mobilität No information |
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Abstract in another language
External factors such as climate change and the current energy crisis due to global conflicts are leading to the increasing relevance of energy consumption and energy procurement in the manufacturing industry. In addition to the growing call for sustainability, companies are increasingly struggling with rising energy costs and the power grid's reliability, which endangers the competitiveness of companies and regions affected by high energy prices. Appropriate measures for energy-efficient and, not least, energy-flexible production are necessary. In addition to innovations and optimizations of plants and processes, digital energy platforms for the visualization, analysis, optimization, and control of energy flows are becoming essential. Over time, several digital energy platforms emerged on the market. The number and the different functionalities of the platforms make it challenging for classic manufacturing companies to keep track of and select the right digital energy platform. The characteristics and functionalities of digital energy platforms have already been identified and structured in literature. However, classifying existing platforms into archetypes makes it easier for companies to select the platforms providing the missing functionality. To tackle this issue, we conducted an explorative and data-driven cluster analysis based on 49 existing digital energy platforms to identify digital energy platform archetypes and derive implications for research and practice. The results show four different archetypes that primarily differ in terms of energy market integration functionalities: Research Driven Energy Platforms, Energy Flexibility Platforms, SaaS-Aggregators / Virtual Power Plants, and (Manufacturing) IoT-Platforms. Decision makers in manufacturing companies will benefit from the archetypes in future analyses as decision support in procurement processes and modifications of digital energy platforms.